Economic Messages in Prescription Drug Advertisements in Medical Journals
Bibliographic record
Abstract
BACKGROUND: The extent to which pharmaceutical companies promote the economic advantages of their products in advertisements in medical journals, and whether such claims are supported by evidence, has not been quantified. Our objectives were to examine how often prescription drug advertisements in leading medical journals contain economic messages, and to determine the types of promotional claims made and whether supporting evidence is provided. METHODS: All prescription drug advertisements appearing in six leading general medical and specialty journals in 3 selected months annually from 1990 to 1999 were reviewed. Using a standard data collection form, two reviewers examined each ad for economic content-including mention of the drug's price, value, cost saving, or cost-effectiveness. RESULTS: Economic messages appeared in 237 (11.1%) of the 2144 advertisements examined. Proportion of ads with economic content has increased over time (P = 0.003). Most frequently, economic ads contained statements that drugs were "less expensive" or "cost less" than alternative treatments (50.6% of economic ads). Supporting evidence for economic claims was clearly reported in 63.7% of cases, and typically referred to published drug prices rather than more detailed economic analysis. Ads for calcium channel blocking agents and ACE inhibitors frequently contained economic messages. CONCLUSIONS: Economic messages about prescription drugs are used in advertisements in leading medical journals and their frequency may be rising. Physicians should be aware of this phenomenon, and its potential impact on their prescribing decisions. More scrutiny of the supporting evidence underlying economic claims by the medical community and regulators may be needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.188 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.018 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".